The DOI matches its Crossref record; 84 of the 86 references it cites were found in a registry or an index.
Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
Abstract
Recent developments promise to increase greatly the popularity of maximum likelihood (ml) as a technique for estimating variance components. Patterson and Thompson (1971) proposed a restricted maximum likelihood (reml) approach which takes into account the loss in degrees of freedom resulting from estimating fixed effects. Miller (1973) developed a satisfactory asymptotic theory for ml estimators of variance components. There are many iterative algorithms that can be considered for computing the ml or reml estimates. The computations on each iteration of these algorithms are those associated with computing estimates of fixed and random effects for given values of the variance components.
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“It is interesting to note that the ReML objective function and the variational energy are formally identical under this model [15],[18].”
From Hierarchical Models in the Brain (2008) · cites this paper as [18]
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“We have discussed static cases of this fixed-form scheme previously and how it reduces to expectation maximisation (EM; [17]) and restricted maximum likelihood (ReML; [18]) for linear models [15].”
From Hierarchical Models in the Brain (2008) · cites this paper as [18]
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Metadata
- Authors
- Harville, D. A.
- Affiliations
- Iowa State University (US)
- Corresponding author
- Harville, David A.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1977-06
- Volume
- 72
- Issue
- 358
- Pages
- 320-338
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W1982585616
- Cited by
- 2,667
- References
- 86
- Citations by year
- 2026: 56 · 2025: 62 · 2024: 72 · 2023: 86 · 2022: 113 · 2021: 73 · 2020: 71 · 2019: 77 · 2018: 75 · 2017: 79 · 2016: 69 · 2015: 76 · 2014: 114 · 2013: 70 · 2012: 109
- FWCI
- 16.91
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the American Statistical Association (publishedVersion)
- Defense Technical Information Center (DTIC) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
- Keywords
- variance component estimation, maximum likelihood estimation, restricted maximum likelihood, fixed and random effects, iterative methods, asymptotic theory, mixed models
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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